Although it is well established that familial Alzheimer disease (AD) has a strong genetic basis, additional Mendelian genes remain to be identified. Mutations in the APP, PSEN1 or PSEN2 genes are involved in minority of AD families and are characterized with early disease onset. Large genome-wide association studies have not found strong evidence for the contribution of common variants besides the APOE gene. Although many families with pedigrees suggestive of autosomal dominant inheritance have been described and linkage studies have found evidence for multiple contributing loci, no new genes have been identified in the last 20 years. The goal of this proposal is to apply novel analytic approaches to identify families in which AD is likely to have a single gene etiology and to utilize next generation sequencing technologies to find these genes. The University of Washington (UW) AD collection contains more than twenty families where pedigrees are consistent with Mendelian inheritance. To identify additional families where single genes are likely to be causal, we will use the existing, well characterized National Institute of Aging (NIA) and National Institute of Mental Health (NIMH) AD collections with more than 700 families. In these collections, for which extensive genotype data is available, we will perform segmental Identity-by-Descent (IBD) mapping and Homozygosity-by-Descent (HBD) analysis to detect families that share a common ancestor within the past three to nine generations. Given the ascertainment of probands based on disease status it is expected that the relatedness uncovered by these analyses reflects inheritance of a shared causal mutation from the recent common ancestor. To identify candidate genes in UW families with pedigrees, and NIA and NIMH families that share recent ancestry as defined by IBD and HBD analyses, we will perform exome capture and massively parallel sequencing followed by bioinformatics analysis and evaluation of co-segregation. To establish association of identified candidate genes with AD we will perform gene-based mutational load case-control studies with more than 200 familial AD cases and 2,000 population controls. Finally, to facilitate validation of our findings we will deposit sequence information in a public database. The identification of novel AD genes would be a significant step towards an increased understanding of the genetic architecture of AD. These genes would enable development of diagnostic tests and implicate new or expanded molecular pathways involved in AD pathogenesis. Examination of these pathways will likely reveal additional therapeutic targets. This study will also establish the utility of our innovative analytical approach combined with exome sequencing as a powerful method for the identification of genes for Mendelian forms of common genetically heterogeneous disorders.